Associate Data Scientist

Responsible for receiving, informing, and executing projects that entail the entire scope of the data science pipeline which include, but are not limited to: integrating disparate and centralized data into data marts, developing statistical models, designing and automating report distribution while continuously presenting and re-assessing results in support of department initiatives. This position will both lead and support interdisciplinary collaboration to identify opportunities and deploy adaptive analytic strategies to provide measurable improvements in the value of care delivered by University Hospitals to current and future patient populations.

• Lead the discovery and requirements gathering process with key clinical and business stakeholders to inform analytic plans
• Collaboratively co-create the discovery, design, development, deployment, optimization, and maintenance of advanced analytics and data science techniques to enrich disparate datasets to craft data-driven interventions aimed at achieving the Quadruple Aim.
• Research, design, develop and implement statistical models, and advanced analytics to support key strategic initiatives.
• Develop and deploy innovative analytic solutions for simplistic Analytics-As-A-Service Business Intelligence dashboards, rapid-fire flash reports directly to clinical and operational colleagues and/or other customized reporting distribution solutions.
• Visualize data in creative ways that brings data and insights to life and is consumable in the business and operational workflow of end-users
• Creatively utilize diverse data sources, such as electronic health record data, insurance claims data, scheduling and financial data, social determinants of health data and any other relevant sources that help support UH Clinical Transformation and System Operations Strategy.
• Develop purpose-driven data marts in Alteryx and SQL environments (on premise and Microsoft Azure).
• Assess the effectiveness and accuracy of new data sources and data gathering techniques
• Collaborate with IT to support data architecture of diverse datasets that support clinical integration by converging these disparate data systems into repositories fit for algorithmic development and model training.
• Evaluate business performance and dynamically monitor critical operational measures related to shared savings arrangements and other value-based programs with governmental and commercial payors.